A Systematic Review of Medical Costs Associated with Heart Failure in the USA (2014–2020)

Urbich, Michael; Pantiri, K; Heisen, Marieke; Bennison, C.; Wirtz, Heidi S.; Tanna, Gian Luca Di

doi:10.1007/s40273-020-00952-0

Cited by 267 publications

(224 citation statements)

References 111 publications

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“…An analysis of HF economic burden worldwide in 2021 estimated the cost of HF to be US$108 billion per annum, with US$65 billon attributed to direct costs and US$43 billon to indirect costs. [ 53 , 54 ]…”

Section: Costs and Barriers To Telemedicine Implementationmentioning

confidence: 99%

The Future of Telemedicine in the Management of Heart Failure Patients

et al. 2021

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Telemedicine (TM) is potentially a way of escalating heart failure (HF) multidisciplinary integrated care. Despite the initial efforts to implement TM in HF management, we are still at an early stage of its implementation. The coronavirus disease 2019 pandemic led to an increased utilisation of TM. This tendency will probably remain after the resolution of this threat. Face-to-face medical interventions are gradually transitioning to the virtual setting by using TM. TM can improve healthcare accessibility and overcome geographic inequalities. It promotes healthcare system efficiency gains, and improves patient self-management and empowerment. In cooperation with human intervention, artificial intelligence can enhance TM by helping to deal with the complexities of multicomorbidity management in HF, and will play a relevant role towards a personalised HF patient approach. Artificial intelligence-powered/telemedical/heart team/multidisciplinary integrated care may be the next step of HF management. In this review, the authors analyse TM trends in the management of HF patients and foresee its future challenges within the scope of HF multidisciplinary integrated care.

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Section: Costs and Barriers To Telemedicine Implementationmentioning

confidence: 99%

The Future of Telemedicine in the Management of Heart Failure Patients

et al. 2021

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“…HF is one of the leading causes of morbidity and mortality worldwide, with a prevalence ranging from 6% to 13% [ 2 ]. An analysis in 2012 estimated that the global cost of HF was $108 billion per year, of which $65 billon was attributed to direct and $43 billion to indirect costs [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Salivary Biomarkers for Diagnosis and Therapy Monitoring in Patients with Heart Failure. A Systematic Review

et al. 2021

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The aim of this study was to perform a systematic review on the potential value of saliva biomarkers in the diagnosis, management and prognosis of heart failure (HF). The correlation between saliva and plasma values of these biomarkers was also studied. PubMed was searched to collect relevant literature, i.e., case-control, cross-sectional studies that either compared the values of salivary biomarkers among healthy subjects and HF patients, or investigated their role in risk stratification and prognosis in HF patients. No randomized control trials were included. The search ended on 31st of December 2020. A total of 15 studies met the inclusion criteria. 18 salivary biomarkers were analyzed and the levels of all biomarkers studied were found to be higher in HF patients compared to controls, except for amylase, sodium, and chloride that had smaller saliva concentrations in HF patients. Natriuretic peptides are the most commonly used plasma biomarkers in the management of HF. Their saliva levels show promising results, although the correlation of saliva to plasma values is weakened in higher plasma values. In most of the publications, differences in biomarker levels between HF patients and controls were found to be statistically significant. Due to the small number of patients included, larger studies need to be conducted in order to facilitate the use of saliva biomarkers in clinical practice.

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“…3,4 In the US, it is estimated that medical care relevant to HF costs more than 30 million annually. 5 The combination of complex presentation and financial burden of HF has made understanding the disease in clinical populations a priority.…”

Section: Introductionmentioning

confidence: 99%

Identifying Heart Failure from Electronic Health Records: A Systematic Evidence Review

Levinson

Malinowski²,

Bielinski

et al. 2021

Preprint

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Background: Heart failure (HF) is a complex syndrome associated with significant morbidity and healthcare costs. Electronic health records (EHRs) are widely used to identify patients with HF and other phenotypes. Despite widespread use of EHRs for phenotype algorithm development, it is unclear if the characteristics of identified populations mirror those of clinically observed patients and reflect the known spectrum of HF phenotypes. Methods: We performed a subanalysis within a larger systematic evidence review to assess the different methods used for HF algorithm development and their application to research and clinical care. We queried PubMed for articles published up to November 2020. Out of 318 studies screened, 25 articles were included for primary analysis and 15 studies using only International Classification of Diseases (ICD) codes were evaluated for secondary analysis. Results are reported descriptively. Results: HF algorithms were most often developed at academic medical centers and the V.A. One health system was responsible for 8 of 10 HF algorithm studies. HF and congestive HF were the most frequent phenotypes observed and less frequently, specific HF subtypes and acute HF. Diagnoses were the most common data type used to identify HF patients and echocardiography was the second most frequent. The majority of studies used rule-based methods to develop their algorithm. Few studies used regression or machine learning methods to identify HF patients. Validation of algorithms varied considerably: only 52.9% of HF and 44.4% of HF subtype algorithms were validated, but 75% of acute HF algorithms were. Demographics of any study population were reported in 68% of algorithm studies and 53% of ICD-only studies. Fewer than half reported demographics of their HF algorithm-identified population. Of those reporting, most identified majority male (>50%) populations, including both algorithms for HF with preserved ejection fraction. Conclusion: There is significant heterogeneity in phenotyping methodologies used to develop HF algorithms using EHRs. Validation of algorithms is inconsistent but largely relies on manual review of patient records. The concentration of algorithm development at one or two sites may reduce potential generalizability of these algorithms to identify HF patients at non-academic medical centers and in populations from underrepresented regions. Differences between the reported demographics of algorithm-identified HF populations those expected based on HF epidemiology suggest that current algorithms do not reflect the full spectrum of HF patient populations.

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A Systematic Review of Medical Costs Associated with Heart Failure in the USA (2014–2020)

Cited by 267 publications

References 111 publications

The Future of Telemedicine in the Management of Heart Failure Patients

The Future of Telemedicine in the Management of Heart Failure Patients

Salivary Biomarkers for Diagnosis and Therapy Monitoring in Patients with Heart Failure. A Systematic Review

Identifying Heart Failure from Electronic Health Records: A Systematic Evidence Review

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